Field
The invention relates to a method for improving the performance of a method for computationally predicting a future state of an object. The invention also regards a respective driver assistance system executing such method, a vehicle including such driver assistance system as well as the program storage medium and a respective program.
Description of the Related Art
Over the last years, driver assistance systems became more and more comfortable. Due to their increased capability of influencing the actuation of car controls such as brakes and/or throttle and/or steering, they became powerful means for assisting a driver. But of course the capability of correctly estimating a traffic situation is limited. This will sometimes lead to wrong evaluations of a scene in which the host vehicle on which such driver assistant system is mounted is part of. There is no question that assisting drivers in making their decisions or directly influencing the driving of the vehicle may improve safety on the roads, in particular in dense traffic conditions. But on the other side, it is also evident that the acceptance of such systems strongly depend on a low number of “wrong” predictions or automated interactions with the controls of the vehicle that do not correspond to the driver's own interpretation of the scene.
One approach to improve acceptance of such systems has been made by introducing the so-called context-based prediction being capable of producing a prediction result on a specific type of behavior which is assumed to be performed by a target object. This context-based prediction is a first prediction step in a prediction system that also uses a so-called physical-prediction. The physical-prediction uses a result of the context-based prediction including information about a specific type of behavior which is predicted to be performed by the target vehicle, and performs a physical prediction based on which the results are confirmed or dismissed and thereby constitutes a second prediction step in the entire prediction method. Such system is described in EP 2 562 060 A1. The benefit of such system is that a future movement behavior of a target object may not be determined only when it has already started, but it may be considered already at a point in time where only analysis of the entire situation allows determining a behavior likely to happen. For example a lane change situation where another vehicle most probably will cut in may be recognized early and thus, the host vehicle could present a warning or could slow down already automatically even before the lane change actually has started in order to avoid harsh braking situations.
As mentioned earlier, such systems will only be accepted by the driver of the host vehicle in case that the interpretation of the scene by the prediction system does not lead to wrong prediction results too often. The acceptance could be improved if the system would be capable to recognize that the usual driver's intention or performed behavior in particular situations deviates from the suggested or performed behavior of the prediction system.
Thus, there is a need to improve the performance of a method for computationally predicting a future state of a target object.